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Oliver Davis (King's College London, London, United Kingdom)
Genome-wide association (GWA) is providing valuable insights into the genomics of complex traits. However, much of the heritability of these traits remains unexplained. Because of the small effect sizes of most variants, identifying them will be a considerable statistical challenge, requiring knowledge of the genetic structure of complex traits. Maximum-likelihood structural equation modelling (SEM) of twin data is one way to explore their genetic aetiology. SEM goes beyond questions of nature and nurture to quantify similarities in the genetic architecture of the traits. The closeness of the genetic relationships can be represented using multidimensional scaling (MDS). We used Groovy scripts and the Mx SEM package to calculate the genetic similarities among multiple measures of reading, mathematics, cognitive ability, and language in 5434 pairs of 12-year-old twins from the UK’s Twins Early Development Study. We performed MDS in R and used OpenGL to plot the genetic distances among the traits in three-dimensional space. The interactive plots highlight subtle patterns of gene-sharing, such as the close genetic relationship between language and cognition, guiding our GWA analy